Fix crash on free variables

include/sleipnir/autodiff/AdjointExpressionGraph.hpp

@@ -107,6 +107,11 @@ class AdjointExpressionGraph {
   /**
    * Returns the variable's gradient tree.
    *
+   * This function lazily allocates variables, so elements of the returned
+   * VariableMatrix will be empty if the corresponding element of wrt had no
+   * adjoint. Ensure Variable::expr isn't nullptr before calling member
+   * functions.
+   *
    * @param wrt Variables with respect to which to compute the gradient.
    */
   VariableMatrix GenerateGradientTree(const VariableMatrix& wrt) const {

include/sleipnir/autodiff/Jacobian.hpp

@@ -45,6 +45,10 @@ class SLEIPNIR_DLLEXPORT Jacobian {
     }
 
     for (int row = 0; row < m_variables.Rows(); ++row) {
+      if (m_variables(row).expr == nullptr) {
+        continue;
+      }
+
       if (m_variables(row).Type() == ExpressionType::kLinear) {
         // If the row is linear, compute its gradient once here and cache its
         // triplets. Constant rows are ignored because their gradients have no

jormungandr/cpp/Docstrings.hpp

@@ -1989,6 +1989,11 @@ Parameter ``row``:
 static const char *__doc_sleipnir_detail_AdjointExpressionGraph_GenerateGradientTree =
 R"doc(Returns the variable's gradient tree.
 
+This function lazily allocates variables, so elements of the returned
+VariableMatrix will be empty if the corresponding element of wrt had
+no adjoint. Ensure Variable::expr isn't nullptr before calling member
+functions.
+
 Parameter ``wrt``:
     Variables with respect to which to compute the gradient.)doc";
 

jormungandr/test/optimization/linear_problem_test.py

@@ -30,3 +30,23 @@ def test_maximize():
 
     assert x.value() == pytest.approx(375.0, abs=1e-6)
     assert y.value() == pytest.approx(250.0, abs=1e-6)
+
+
+def test_free_variable():
+    problem = OptimizationProblem()
+
+    x = problem.decision_variable(2)
+    x[0].set_value(1.0)
+    x[1].set_value(2.0)
+
+    problem.subject_to(x[0] == 0)
+
+    status = problem.solve(diagnostics=True)
+
+    assert status.cost_function_type == ExpressionType.NONE
+    assert status.equality_constraint_type == ExpressionType.LINEAR
+    assert status.inequality_constraint_type == ExpressionType.NONE
+    assert status.exit_condition == SolverExitCondition.SUCCESS
+
+    assert x[0].value() == pytest.approx(0.0, abs=1e-6)
+    assert x[1].value() == pytest.approx(2.0, abs=1e-6)

test/src/optimization/LinearProblemTest.cpp

@@ -33,3 +33,23 @@ TEST_CASE("LinearProblem - Maximize", "[LinearProblem]") {
   CHECK(x.Value() == Catch::Approx(375.0).margin(1e-6));
   CHECK(y.Value() == Catch::Approx(250.0).margin(1e-6));
 }
+
+TEST_CASE("LinearProblem - Free variable", "[LinearProblem]") {
+  sleipnir::OptimizationProblem problem;
+
+  auto x = problem.DecisionVariable(2);
+  x(0).SetValue(1.0);
+  x(1).SetValue(2.0);
+
+  problem.SubjectTo(x(0) == 0);
+
+  auto status = problem.Solve({.diagnostics = true});
+
+  CHECK(status.costFunctionType == sleipnir::ExpressionType::kNone);
+  CHECK(status.equalityConstraintType == sleipnir::ExpressionType::kLinear);
+  CHECK(status.inequalityConstraintType == sleipnir::ExpressionType::kNone);
+  CHECK(status.exitCondition == sleipnir::SolverExitCondition::kSuccess);
+
+  CHECK(x(0).Value() == Catch::Approx(0.0).margin(1e-6));
+  CHECK(x(1).Value() == Catch::Approx(2.0).margin(1e-6));
+}